A better way to measure household income in London

London’s a city of huge contrast – particularly in terms of the income levels of its 3.4 million households. Here at City Hall, we know household income’s very hard to measure accurately. Household structures can be complex, and even if people are happy to disclose their yearly household income, they don’t always know the overall figure.

With that in mind, it’s not surprising that official measures of household income for local areas are hard to come by. A few large companies collect income data (from things like store cards, and returned product guarantee cards). However, they don’t share the results of their findings for free. There are also strict limits on how the results can be passed onto others.

We know that household income data is sought after. It’s one of the most commonly searched for terms on London Datastore. So for the first time we’re publishing household income estimates for a range of local areas. This has been made possible by a combination of reliable household income estimates at regional level from the Understanding Society study, and other small area indicators taken from, among other sources, the 2011 Census.

It will hardly come as a shock that the ward with the highest average household income is Knightsbridge and Belgravia (Westminster), but there are some surprises. Did you know that both Westminster and Kensington and Chelsea have a ward in the bottom ten ranked wards for median household income? This helps explains why these two boroughs have the largest spread of incomes in London. However, there is much income variation in other London boroughs, which shows how Londoners from very different economic backgrounds live cheek by jowl.

Alternatively, visit Talk London where you can explore how household income compares with household spending in London. You may want to try out an interactive calculator, where you can input your income and expenditure and see how much you will, or won’t, be left with and how this compares with the London average.

We also welcome your feedback, comments and views on the methods we used to put together the estimates, and will use it to improve any future releases.